Name: saccharomyces cerevisiae exponential growth kinetics in batch culture to analyze respiratory and fermentative metabolism
Uploaded: 2018-09-30T14:00:00
Description: Watch this Scientific Journal Video about Saccharomyces cerevisiae Exponential Growth Kinetics in Batch Culture to Analyze Respiratory and Fermentative Metabolism at JoVE.com

This project was supported by grants of the Consejo Nacional de Ciencia y Tecnolog&#237;a (grant number 293940) and Fundaci&#243;n TELMEX-TELCEL (grant number 162005585), both to IKOM.

1. Culture Media and Inoculum Preparation
<ol>
	<li>Prepare 100 mL of 2% yeast extract-peptone-dextrose (YPD) liquid medium (add 1 g of yeast extract, 2 g of casein peptone, and 2 g of glucose to 100 mL of distilled water). Dispense 3 mL of the media into 15 mL sterilizable conical tubes. Autoclave the media for 15 min at 121 &#176;C and 1.5 psi. 
	NOTE: The media can be stored for up to one month at 4&#8211;8 &#176;C.</li>
	<li>Inoculate a conical tube filled with 3 mL of cool sterile 2% YPD broth with 250 &#956;...

<ol>
	<li>Parrella, E., Longo, V. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+chronological+life+span+of+Saccharomyces+cerevisiae+to+study+mitochondrial+dysfunction+and+disease.">The chronological life span of Saccharomyces cerevisiae to study mitochondrial dysfunction and disease.</a> Methods. 46 (4), 256-262 (2008).</li><li>Rosas Lemus, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+role+of+glycolysis-derived+hexose+phosphates+in+the+induction+of+the+Crabtree+effect.">The role of glycolysis-derived hexose phosphates in the induction of the Crabtree effect.</a> Journal of Biological Chemistry. , (2018).</li><li>Xu, X. D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Warburg+effect+or+reverse+Warburg+effect?+A+review+of+cancer+metabolism.">Warburg effect or reverse Warburg effect? A review of cancer metabolism.</a> Oncology Research and Treatment. 38 (3), 117-122 (2015).</li><li>De Deken, R. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Crabtree+effect:+a+regulatory+system+in+yeast.">The Crabtree effect: a regulatory system in yeast.</a> Journal of General Microbiology. 44 (2), 149-156 (1966).</li><li>Hagman, A., Sall, T., Piskur, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+the+yeast+short-term+Crabtree+effect+and+its+origin.">Analysis of the yeast short-term Crabtree effect and its origin.</a> The FEBS Journal. 281 (21), 4805-4814 (2014).</li><li>Hammad, N., Rosas-Lemus, M., Uribe-Carvajal, S., Rigoulet, M., Devin, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Crabtree+and+Warburg+effects:+Do+metabolite-induced+regulations+participate+in+their+induction?.">The Crabtree and Warburg effects: Do metabolite-induced regulations participate in their induction?.</a> Biochim Biophys Acta. 1857 (8), 1139-1146 (2016).</li><li>Keating, E., Martel, F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Antimetabolic+Effects+of+Polyphenols+in+Breast+Cancer+Cells:+Focus+on+Glucose+Uptake+and+Metabolism.">Antimetabolic Effects of Polyphenols in Breast Cancer Cells: Focus on Glucose Uptake and Metabolism.</a> Frontiers in Nutrition. 5, 25 (2018).</li><li>Pfeiffer, T., Morley, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+evolutionary+perspective+on+the+Crabtree+effect.">An evolutionary perspective on the Crabtree effect.</a> Frontiers in Molecular Biosciences. 1, 17 (2014).</li><li>Olivares-Marin, I. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Interactions+between+carbon+and+nitrogen+sources+depend+on+RIM15+and+determine+fermentative+or+respiratory+growth+in+Saccharomyces+cerevisiae.">Interactions between carbon and nitrogen sources depend on RIM15 and determine fermentative or respiratory growth in Saccharomyces cerevisiae.</a> Applied Microbiology and Biotechnology. 102 (10), 4535-4548 (2018).</li><li>Monod, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+growth+of+bacterial+cultures.">The growth of bacterial cultures.</a> Annual Review of Microbiology. 3 (1), 371-394 (1949).</li><li>Cui, S., Xu, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Analysis+of+mathematical+models+for+the+growth+of+tumors+with+time+delays+in+cell+proliferation.">Analysis of mathematical models for the growth of tumors with time delays in cell proliferation.</a> Journal of Mathematical Analysis and Applications. 336 (1), 523-541 (2007).</li><li>Benzekry, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Classical+mathematical+models+for+description+and+prediction+of+experimental+tumor+growth.">Classical mathematical models for description and prediction of experimental tumor growth.</a> Public Library of Science Computational Biology. 10 (8), e1003800 (2014).</li><li>Ramos-Gomez, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Resveratrol+induces+mitochondrial+dysfunction+and+decreases+chronological+life+span+of+Saccharomyces+cerevisiae+in+a+glucose-dependent+manner.">Resveratrol induces mitochondrial dysfunction and decreases chronological life span of Saccharomyces cerevisiae in a glucose-dependent manner.</a> Journal of Bioenergetics and Biomembranes. 49 (3), 241-251 (2017).</li><li>Madrigal-Perez, L. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Energy-dependent+effects+of+resveratrol+in+Saccharomyces+cerevisiae.">Energy-dependent effects of resveratrol in Saccharomyces cerevisiae.</a> Yeast. 33 (6), 227-234 (2016).</li><li>Peleg, M., Corradini, M. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Microbial+growth+curves:+what+the+models+tell+us+and+what+they+cannot.">Microbial growth curves: what the models tell us and what they cannot.</a> Critical Reviews in Food Science and Nutrition. 51 (10), 917-945 (2011).</li></ol>

A long time has passed since J. Monod10 expressed that the study of the growth of bacterial cultures is the basic method of microbiology. The advent of the molecular tools delays the usage and study of the growth as a technique. Despite the complexity of growth which involves numerous interrelated processes, its underlying mechanisms can be described by using mathematical models11. This is a robust approach that can be used as a complementary tool to elucidate the most intr...

Saccharomyces cerevisiae growth has served as a valuable tool to identify dozens of physiological and molecular mechanisms. Growth is measured primarily by three methods: serial dilutions for spot testing, colony-forming unit counting, and growth curves. These techniques can be used alone or in combination with a variety of substrates, environmental conditions, mutants, and chemicals to investigate specific responses or phenotypes.
Mitochondrial respiration is a biological process in which growth kinetics has been successfully applied for discovering unknown mechanisms. In this case, the supplementation of growth media with non-fermentable carbon sources such as glycerol, lactate, or ethanol (which are exclusively metabolized by mitochondrial respiration), as the sole carbon and energy source allows for evaluating the respiratory growth, which is important to detect perturbations in oxidative phosphorylation activity1. On the other hand, it is complicated to use growth kinetic models as a method for deciphering the mechanisms behind fermentation.
The study of fermentation and mitochondrial respiration is essential to elucidate the molecular mechanisms behind certain phenotypes such as the Crabtree and Warburg effects2,3. The Crabtree effect is characterized by an increase of glycolytic flux, repression of mitochondrial respiration, and establishment of fermentation as the primary pathway to generate ATP in the presence of high concentrations of fermentable carbohydrates (&#62;0.8 mM)4,5. The Warburg effect is metabolically analog to the Crabtree effect, with the difference being that in mammalian cells, the main product of fermentation is lactate6. Indeed, the Warburg effect is exhibited by a variety of cancer cells, triggering glucose uptake and consumption even in the presence of oxygen7. Thereby, studying the molecular basis of the switch from respiration to fermentation in the Crabtree effect has both biotechnological repercussions (for ethanol production) and potential impacts in cancer research.
S. cerevisiae growth may be a suitable tool to study the Crabtree and Warburg effects. This idea is based on the fact that in the yeast exponential phase, the central pathways used to produce ATP are mitochondrial respiration and fermentation, which are essential to sustain growth. For instance, the growth of S. cerevisiae is intimately related to the function of ATP-generating pathways. In S. cerevisiae, the mitochondrial respiration produces approximately 18 ATP molecules per glucose molecule, whereas fermentation only generates 2 ATP molecules, hence it is expected that the growth rate has tight links with the metabolic pathways producing ATP8. In this regard, when fermentation is the principal route to generate ATP, the yeast compensates for the low ATP production by increasing the rate of glucose uptake. On the contrary, the glucose consumption by yeast cells that use mitochondrial respiration as the main ATP source is low. This indicates that it is important for the yeast to sense carbohydrate availability before determining how ATP will be generated. Therefore, glucose availability plays an important role in the switch between fermentation and mitochondrial respiration in S. cerevisiae. In the presence of high quantities of glucose, the yeast prefers fermentation as the central route to generate ATP. Interestingly, when the yeast is fermenting, the specific growth rate is maintained at its maximum. On the other hand, under low levels of glucose, S. cerevisiae produces ATP using mitochondrial respiration, maintaining lower growth rates. Thereby, variation in the concentration of glucose and the use of other carbon sources induce changes in the yeast&#39;s preference between fermentative and respiratory growth. By taking into account this fact with the exponential growth equation, one can obtain the biological meaning of kinetic parameters such as doubling time (Dt) and specific growth rate (&#181;). For example, lower &#181; values were found when the yeast uses mitochondrial respiration as the primary pathway. On the contrary, under conditions that favor fermentation, higher &#181; values were found. This methodology may be used to measure the probable mechanisms of any chemicals affecting fermentation and mitochondrial respiration in S. cerevisiae.
The objective of this paper is to propose a method based on growth kinetics for screening the effects of a given substance/compound on mitochondrial respiration or fermentation.

<table border="0" cellpadding="0" cellspacing="0" width="573">
	<tbody>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Orbital Shaker</td>
			<td style="width:71px;">Thermo Scientific</td>
			<td align="right" style="width:119px;">4353</td>
			<td style="width:167px;">For inoculum incubation or conical fask cultures</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Bioscreen&#160;</td>
			<td style="width:71px;">Growth curves</td>
			<td style="width:119px;">C MBR</td>
			<td>For batch cultures in microplates</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Glucose</td>
			<td style="width:71px;">Sigma&#160;</td>
			<td style="width:119px;">G7021</td>
			<td>For YPD broth preparation</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Peptone from casein, enzymatic digest</td>
			<td style="width:71px;">Sigma&#160;</td>
			<td align="right" style="width:119px;">82303</td>
			<td>For YPD broth preparation</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Yeast extract</td>
			<td style="width:71px;">Sigma&#160;</td>
			<td style="width:119px;">09182-1KG-F</td>
			<td>For YPD broth preparation</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Bacteriological Agar</td>
			<td style="width:71px;">Sigma&#160;</td>
			<td style="width:119px;">A5306</td>
			<td>For YPD agar preparation</td>
		</tr>
		<tr height="25">
			<td height="25" style="height:25px;">NaH2PO4</td>
			<td style="width:71px;">Sigma&#160;</td>
			<td>S8282</td>
			<td>For SC broth preparation</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">(NH4)2SO4</td>
			<td style="width:71px;">Sigma&#160;</td>
			<td>A4418</td>
			<td>For SC broth preparation</td>
		</tr>
		<tr height="63">
			<td height="63" style="height:63px;width:216px;">Yeast nitrogen base without amino acids and ammonium sulfate</td>
			<td style="width:71px;">Sigma&#160;</td>
			<td style="width:119px;">Y1251</td>
			<td>For SC broth preparation</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Yeast synthetic drop-Out medium supplements</td>
			<td style="width:71px;">Sigma&#160;</td>
			<td style="width:119px;">Y1501</td>
			<td>For SC broth preparation</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Ammonium sulfate granular</td>
			<td style="width:71px;">J.T. Baker</td>
			<td style="width:119px;">0792-R</td>
			<td>For medium supplementation example</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Resveratrol</td>
			<td style="width:71px;">Sigma&#160;</td>
			<td style="width:119px;">R5010</td>
			<td>For medium supplementation example</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Galactose</td>
			<td style="width:71px;">Sigma&#160;</td>
			<td>G8270</td>
			<td>For medium supplementation example</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Sucrose</td>
			<td style="width:71px;">Sigma&#160;</td>
			<td style="width:119px;">S7903</td>
			<td>For medium supplementation example</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Absolut ethanol</td>
			<td style="width:71px;">Merck</td>
			<td align="right">107017</td>
			<td>For medium supplementation example</td>
		</tr>
		<tr height="21">
			<td height="21" style="height:21px;width:216px;">Glycerol</td>
			<td style="width:71px;">J.T. Baker</td>
			<td>2136-01</td>
			<td>For medium supplementation example</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">GraphPad Prism</td>
			<td style="width:71px;">GraphPad Software</td>
			<td></td>
			<td>For data analysis</td>
		</tr>
		<tr height="42">
			<td height="42" style="height:42px;width:216px;">Honeycomb microplates</td>
			<td style="width:71px;">Thermo Scientific</td>
			<td align="right">9502550</td>
			<td>For microplate cultures</td>
		</tr>
	</tbody>
</table>

saccharomyces cerevisiae exponential growth kinetics in batch culture to analyze respiratory and fermentative metabolism

Saccharomyces cerevisiae cells in the exponential phase sustain their growth by producing ATP through fermentation and/or mitochondrial respiration. The fermentable carbon concentration mainly governs how the yeast cells generate ATP; thus, the variation in fermentable carbohydrate levels drives the energetic metabolism of S. cerevisiae. This paper describes a high-throughput method based on exponential yeast growth to estimate the effects of concentration changes and nature of the carbon source on respiratory and fermentative metabolism. The growth of S. cerevisiae is measured in a microplate or shaken conical flask by determining the optical density (OD) at 600 nm. Then, a growth curve is built by plotting OD versus time, which allows identification and selection of the exponential phase, and is fitted with the exponential growth equation to obtain kinetic parameters. Low specific growth rates with higher doubling times generally represent a respiratory growth. Conversely, higher specific growth rates with lower doubling times indicate fermentative growth. Threshold values of doubling time and specific growth rate are estimated using well-known respiratory or fermentative conditions, such as non-fermentable carbon sources or higher concentrations of fermentable sugars. This is obtained for each specific strain. Finally, the calculated kinetic parameters are compared with the threshold values to establish whether the yeast shows fermentative and/or respiratory growth. The advantage of this method is its relative simplicity for understanding the effects of a substance/compound on fermentative or respiratory metabolism. It is important to highlight that growth is an intricate and complex biological process; therefore, preliminary data from this method must be corroborated by the quantification of oxygen consumption and accumulation of fermentation byproducts. Thereby, this technique can be used as a preliminary screening of compounds/substances that may disturb or enhance fermentative or respiratory metabolism.

Growth curves can be used to preliminarily discriminate between respiratory and fermentative phenotypes in the S. cerevisiae yeast. Therefore, we performed batch cultures of S. cerevisiae (BY4742) with different glucose concentrations that have been reported to induce fermentative growth: 1%, 2%, and 10% (w/v)9. Cultures showing a fermentative phenotype have a small lag phase and an exponential phase with a high growth rate (F...

Watch this Scientific Journal Video about Saccharomyces cerevisiae Exponential Growth Kinetics in Batch Culture to Analyze Respiratory and Fermentative Metabolism at JoVE.com

Saccharomyces cerevisiae Exponential Growth Kinetics in Batch Culture to Analyze Respiratory and Fermentative Metabolism

Here we present a protocol to estimate the respiratory and fermentative metabolism by fitting the exponential growth of Saccharomyces cerevisiae to the exponential growth equation. Calculation of the kinetic parameters allows for the screening of influences of substances/compounds on fermentation or mitochondrial respiration.

Saccharomyces cerevisiae Exponential Growth Kinetics in Batch Culture to Analyze Respiratory and Fermentative Metabolism

Saccharomyces cerevisiae cells in the exponential phase sustain their growth by producing ATP through fermentation and/or mitochondrial respiration. The ...

This method can help answer key questions in the biotechnological and biomedical fields such as what are the molecular basis behind the Warburg and the Crabtree effects. The main advantage of this technique is that it allows the high throughput study of the effects of certain substances in respiratory and fermentative metabolism. Begin by inoculating a 15-milliliter conical tube containing three milliliters of cool, sterile 2%yeast extract peptone dextrose, or YPD broth, with 250 microliters of S.cerevisiae yeast cells preserved in glycerol at negative 20 degrees Celsius.Incubate the yeast overnight in an orbital shaker at 30 degrees Celsius and 200 rpm. for streaking onto a 60-milliliter, 2%YPD agar-filled Petri dish the next morning. Culture the dish at 30 degrees Celsius until isolated colonies are observed.Then inoculate a single isolated colony in a new conical tube containing 10 milliliters of cool, sterile 2%YPD broth for overnight culture at 30 degrees Celsius with shaking. For microplate growth-curve setup, add 145 microliters of an appropriate experimental cultural medium to each well of a sterile 10-by-10 well microplate with a lid and inoculate each well with five microliters of the overnight culture. Then incubate the multi-well plate in a microplate reader at 30 degrees Celsius with constant agitation at 200 rpm for 48 hours, measuring the optical density at 600 nanometers every 30 or 60 minutes.For shaken conical flask growth-curve setup, inoculate 20 milliliter conical flasks containing 4.8 milliliters of an appropriate sterile culture media with 200 microliters of pre-inoculum culture at a 600 nanometer optical density of two for incubation at 30 degrees Celsius and 250 rpm. Agitation at 250 revolutions per minute is critical to achieve a suitable growth in low concentrations of carbon sources that exert respiratory growth as we have observed a reduced yeast growth in respiratory conditions at lower agitation speeds. To allow measurement of the optical density at 600 nanometer every two hours for 24 hours, dilute 100 microliters of the shaken conical flask culture in 900 microliters of distilled water in a one-milliliter spectrophotometer cuvette and gently mix by pipette.For data processing, in an appropriate statistical package software, create a new project file, open the new table and graph menu, and select XY.Under the sample data menu, select start with an empty data table and a points and connecting line graph. Leave the X section unselected in subcolumns for replicates or error values. In the Y section, select enter 10 replicate values in side-by-side subcolumns and plot mean and error SD.Then click create.Enter the time at which the OD measurements were obtained in the X column and the OD values obtained from the cultures in the Y column. To identify the exponential growth phase transforming the Y column data into logarithms, click analyze and select the transform analysis. Use Y equals log Y to select the Y values and open the gallery of results.Select the transform data table, click analyze, and select the linear regression analysis, excluding the optical density values that do not follow a linear trend by selecting the values in the table and depressing control and E.In the data-tables gallery, select the data one table and click analyze. Select the nonlinear regression curve fit analysis and the data sets to analyze, and click OK.Then apply least squares fit to the data, leaving the interpolate section unselected, and click OK.Next, open a new project file, and in the new table and graph menu, select the column choice, start with an empty data table, and the desired graph. Set the graph to plot the mean with the standard deviation, and click create.Copy the mean or delta time values from the nonlinear fit results table in the gallery of results and paste the data into a column. Finally, click analyze and select the analysis of interest in the column analyses menu to compare the kinetic parameters of the different nutrimental conditions. The growth kinetic threshold values vary between strengths and must be evaluated according to the conditions that we use in the analysis.Cultures demonstrating a fermentative phenotype have a small lag phase and an exponential phase with a high growth rate. Cultures that obtain energy mainly by oxidative phosphorylation exhibit a longer lag phase with a slow rate of growth during the exponential phase. Calculation of the specific growth rate and doubling time of the growth curves using the exponential growth equation allows for the setting of thresholds for the respiratory and fermentative growth values.For example, in these representative experiments, the effects of different resveratrol concentrations on S.cerevisiae BY4742 cells reveal the modification of the cell energetic status in response to varying glucose concentrations. Here, supplementation with 10%glucose demonstrates that lower concentrations of ammonium favor fermentative metabolism as evidenced by an extended exponential growth phase in these cultures, while a higher concentration induces a respiro-fermentative metabolism as evidenced by an extended lag phase and a slower growth rate during the exponential phase. Finally, robust differences in fermentative doubling-time values can be observed between these two different yeast strains grown under the same conditions, highlighting the necessity of validating the doubling-time threshold for each strain analyzed.While attempting this procedure, it's important to remember that this protocol is only used to screen out phenotype. The specific effects on respiration and fermentation must be confirmed by oxygen consumption assays or by the accumulation of fermentation byproducts respectively.

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